TY - GEN
T1 - Test methodology development for biological agent detection systems
AU - Samuels, Alan C.
AU - Santarpia, Joshua L.
AU - Bottiger, Jerold R.
AU - Hunter, Scott
AU - Stuebing, Edward W.
PY - 2006
Y1 - 2006
N2 - Optical detection systems play a vital role in the early warning detection of airborne biological agents. Fluorescence and elastic scattering signals have been historically exploited in order to characterize and profile bioaerosols and yield information that can help suggest the occurrence of a biological attack. More recently, other optical methods, including Raman, infrared, and laser-induced breakdown spectroscopy, have shown promise as candidate bioaerosol detection systems. The selection of an optimal approach involves careful consideration of advantages and disadvantages among these various alternative optical methods. Key considerations are detection probability, false alarm rate, time to detect, and sensitivity. These four parameters are interrelated functions of the nature of the optical signal - characterized by absorption and/or emission cross-section, information content, and signal measurement system technology limitations. Evaluation of prototype systems that exploit optical signatures to detect and warn of the presence of biological aerosols involves a careful, deliberate process of developing a standardized aerosol challenge that mimics the properties of not only a biological agent release, but also the highly complex natural and anthropogenic aerosol background. The key to developing a test methodology involves 1) interpretation of the limited background aerosol data, 2) development of dynamic aerosol challenge capabilities, and 3) integration of experimental design principles in the development and execution of artificial challenge tests and in the reduction and interpretation of sensor system performance based on the test results.
AB - Optical detection systems play a vital role in the early warning detection of airborne biological agents. Fluorescence and elastic scattering signals have been historically exploited in order to characterize and profile bioaerosols and yield information that can help suggest the occurrence of a biological attack. More recently, other optical methods, including Raman, infrared, and laser-induced breakdown spectroscopy, have shown promise as candidate bioaerosol detection systems. The selection of an optimal approach involves careful consideration of advantages and disadvantages among these various alternative optical methods. Key considerations are detection probability, false alarm rate, time to detect, and sensitivity. These four parameters are interrelated functions of the nature of the optical signal - characterized by absorption and/or emission cross-section, information content, and signal measurement system technology limitations. Evaluation of prototype systems that exploit optical signatures to detect and warn of the presence of biological aerosols involves a careful, deliberate process of developing a standardized aerosol challenge that mimics the properties of not only a biological agent release, but also the highly complex natural and anthropogenic aerosol background. The key to developing a test methodology involves 1) interpretation of the limited background aerosol data, 2) development of dynamic aerosol challenge capabilities, and 3) integration of experimental design principles in the development and execution of artificial challenge tests and in the reduction and interpretation of sensor system performance based on the test results.
KW - Aerosol
KW - Aerosol spectroscopy
KW - Bioagent detection
KW - Biological agent
KW - False alarm rate
KW - Optical detector
KW - Sensor metrics
KW - Sensor performance testing
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U2 - 10.1117/12.686715
DO - 10.1117/12.686715
M3 - Conference contribution
AN - SCOPUS:33846254084
SN - 0819464767
SN - 9780819464767
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Chemical and Biological Sensors for Industrial and Environmental Monitoring II
T2 - Chemical and Biological Sensors for Industrial and Environmental Monitoring II
Y2 - 3 October 2006 through 4 October 2006
ER -